deeppapernotelisted

# DeepPaperNote Use this skill when the user wants one outcome: - read one paper carefully - generate a high-quality Markdown note - save the note into an Obsidian-style vault when configured, or into the current workspace when no vault is configured Chinese trigger examples: - `给这篇论文生成深度笔记` - `写一篇高质量论文精读笔记` - `把这篇文章整理成 obsidian 笔记` - `读这篇论文并生成 md 笔记` This skill is intentionally narrow: - it handles one paper at a time - it does not update daily reading lists - it does not treat a shallow abstract rewrite as a successful output - it does not split the public entrypoint into separate setup, troubleshooting, or start commands ## Core Standard The finished note must be more than a summary. It should reconstruct the paper's argument: - what problem it solves - how the task is defined - what data or materials it uses - how the method or analysis actually works - what results matter most - what the paper does not prove - why the paper is worth keeping Default writer persona: - a top-tier researcher or algorithm engineer - writing a replication-oriented lab note - not writing a popular-science explanation - assuming the reader can follow Python, PyTorch, training loops, and evaluation logic The note must adapt to the paper type. Use the same base structure, but shift emphasis for AI methods, benchmarks, clinical studies, and humanities or social-science papers. ## Workflow Follow this order: 1. resolve the paper identity 2. collect metadata 3. acquire the best available PDF